Description This role also focuses on improving how data-related work gets done by identifying repetitive tasks and implementing practical automation wherever possible. Success depends on strong attention to detail, comfort with routine and repetitive processes, and the ability to analyse, structure, and deliver high-quality data outputs in a timely, dependable manner for internal users. LI-SD2 LI-Hybrid Responsibilities Work on multiple data-related initiatives and requests simultaneously, managing priorities according to operational needs and defined Service Level Agreement (SLA). Extract data from multiple sources, including internal systems, databases, and structured files. Clean, validate, and standardize datasets to ensure data accuracy, consistency, and completeness. Execute bidirectional data preparation processes (tool ↔ template) in line with defined Standard Operating Procedures (SOP) and data mappings. Maintain and update operational datasets, trackers, and reporting outputs. Prepare and deliver recurring and ad-hoc data outputs to Operations stakeholders. Support data submissions, uploads, and scheduled data deliveries. Collaborate closely with Operations teams to understand data requirements and improve data usability. Identify inefficiencies in data processes and propose improvements. Ensure correct handling of sensitive and operationally critical data. Document data processes, transformations, and reporting logic. Perform basic data analysis to identify anomalies, gaps, or inconsistencies. Assessment and improvement of working methodologies (Lean Six Sigma) Document data processes, transformations, SOPs and reporting Qualifications •Education in Data Science, Computer Science, IT, Engineering, Mathematics, or related fields or equivalent practical experience. • Ability to understand, analyse, and work with large volumes of data, identifying anomalies, inconsistencies, and data quality issues. • Understanding of data manipulation concepts, data structures, and basic analytics. • Experience working with structured datasets and operational data is desirable • Basic knowledge of databases and data querying (e.g. SQL) is desirable. • Familiarity with data processing tools and scripting languages (e.g. Python, or similar) is a plus. • Understanding of Agile methodologies and experience working within agile teams (stand-ups, planning, retrospectives) is desirable • Experience working with task and issue tracking tools (e.g. Jira, Confluence or similar). • Strong attention to detail and focus on data accuracy and reliability is essential • Ability to work as a team player with local and offshore teams. • Self-motivated and manage priorities under deadlines. • Effective communication skills, both verbal and written English. Other useful experience (not required): • Familiarity with Atlassian tools such as Jira and Confluence for task tracking and documentation. • Experience working with data analysis or reporting tools (e.g. Excel, Power BI, or similar). • Experience handling large datasets in operational or business environments. • Proficiency in MS Access, and Excel. • Knowledge of the Operations, Healthcare, Insurance, or regulated industries is a plus.